Archived link: https://archive.ph/Vjl1M
Here’s a nice little distraction from your workday: Head to Google, type in any made-up phrase, add the word “meaning,” and search. Behold! Google’s AI Overviews will not only confirm that your gibberish is a real saying, it will also tell you what it means and how it was derived.
This is genuinely fun, and you can find lots of examples on social media. In the world of AI Overviews, “a loose dog won’t surf” is “a playful way of saying that something is not likely to happen or that something is not going to work out.” The invented phrase “wired is as wired does” is an idiom that means “someone’s behavior or characteristics are a direct result of their inherent nature or ‘wiring,’ much like a computer’s function is determined by its physical connections.”
It all sounds perfectly plausible, delivered with unwavering confidence. Google even provides reference links in some cases, giving the response an added sheen of authority. It’s also wrong, at least in the sense that the overview creates the impression that these are common phrases and not a bunch of random words thrown together. And while it’s silly that AI Overviews thinks “never throw a poodle at a pig” is a proverb with a biblical derivation, it’s also a tidy encapsulation of where generative AI still falls short.
I mean are you asking it if there is a history of an idiom existing or just what the idiom could mean?
3 ways to skin a horse
The saying “you can’t cross over a duck’s river” is a play on words, suggesting that it’s difficult to cross a river that is already filled with ducks. It’s not a literal statement about rivers and ducks, but rather an idiom or idiom-like phrase used to express the idea that something is difficult or impossible to achieve due to the presence of obstacles or challenges.
I used the word “origin” instead of “meaning”, which didn’t seem to work.
I am not saying other generative AI lack flaws, but Google’s AI Overview is the most problematic generative AI implementation I have ever seen. It offends me that a company I used to trust continues to force this lie generator as a top result for the #1 search engine. And to what end? Just to have a misinformed populace over literally every subject!
OpenAI has issues as well, but ChatGPT is a much, much better search engine with far fewer hallucinations per answer. Releasing AI Overview while the competition is leagues ahead on the same front is asinine!
Its a language model not a dictionary. By putting the term “definition” before the sentence you imply that the following sentence has a definintion, hence it vectors down to the most likely meaning.
Buddy, I never said the word definition
They famously taught it on Reddit. So it’s not surprising that it just comes up with nonsense.
You would have thought that they would use a more stable data set. Although it does mean it’s very good at explaining the plots of movies badly.
And to what end? Just to have a misinformed populace over literally every subject!
This is a feature; not a bug. We’re entering a new dark age, and generative AI is the tool that will usher it in. The only “problem” generative AI is efficiently solving is a populace with too much access to direct and accurate information. We’re watching as perfectly functional tools and services are being rapidly replaced by a something with inherent issues with reliability, ethics and accountability.
In the case with Google AI overview, I 1000% agree. I am not against all AI tools, but that company has clearly chosen evil.
I’ve resorted to appending every Google search with “-ai” because I don’t want to see their bullshit summaries. Outsourcing our thinking is lazy and dangerous, especially when the technology is so flawed.
I like that trick, noted! I mostly use DuckDuckGo as a browser and search engine now. If it fails I use ChatGPT
Saying you used to trust google is really a core part of the problem. Google isn’t a person. Just like AI isn’t a person. They both do what they are tasked with. Companies prioritize profit. AI prioritizes giving an answer, not necessarily a correct one. That is how it was designed.
Impressive how we seem to agree with each other yet you still found a way to insult my way of putting it
The saying “you can’t butter a fly” is an idiom expressing that someone or something is too difficult to influence or manipulate. It’s rooted in the idea that butterflies, with their delicate nature, are virtually impossible to convince to do anything against their will, let alone “butter” them in a literal sense.
This is a great example - it kinda makes sense if you skim read it but butterflies have nothing to do with butter, just like hotdogs have nothing to do with dogs.
No, that phrase means “this situation is hopeless because the person is incapable of change”. You can’t turn a fly into a butterfly, no matter how hard you try.
That is a fascinating take on the general reaction to LLMs. Thanks for posting this!
Honestly, I’m kind of impressed it’s able to analyze seemingly random phrases like that. It means its thinking and not just regurgitating facts. Because someday, such a phrase could exist in the future and AI wouldn’t need to wait for it to become mainstream.
It’s not thinking. It’s just spicy autocomplete; having ingested most of the web, it “knows” that what follows a question about the meaning of a phrase is usually the definition and etymology of that phrase; there aren’t many examples online of anyone asking for the definition of a phrase and being told “that doesn’t exist, it’s not a real thing.” So it does some frequency analysis (actually it’s probably more correct to say that it is frequency analysis) and decides what the most likely words to come after your question are, based on everything it’s been trained on.
But it doesn’t actually know or think anything. It just keeps giving you the next expected word until it meets its parameters.
Tried “two bananas doesn’t make a balloon meaning origin” and got a fairly plausible explanation for that old saying that I’m sure everyone is familiar with
The saying “better a donkey than an ass” plays on the dual meaning of the word “ass.” It suggests that being called a donkey is less offensive than being called an ass, which can be used as an insult meaning stupid or foolish. The phrase highlights the contrast between the animal donkey, often seen as a hardworking and steady companion, and the derogatory use of “ass” in everyday language.
Yep, it does work
Better a pineapple thananananas…
Didn’t work for me. A lot of these ‘gotcha’ AI moments seem to only work for a small percentage of users, before being noticed and fixed. Not including the more frequent examples that are just outright lies, but get upvoted anyway because ‘AI bad’
It looks like incognito and adding “meaning AI” really gets it to work just about every time for me
However, “the lost dog can’t lay shingles meaning” didn’t work with or without “AI”, and “the lost dog can’t lay tiles meaning” only worked when adding “AI” to the end
So it’s a gamble on how gibberish you can make it I guess
Now I’ll never know what people mean when they say “those cupcakes won’t fill a sauna”!
I found that trying “some-nonsense-phrase meaning” won’t always trigger the idiom interpretation, but you can often change it to something more saying-like.
I also found that trying in incognito mode had better results, so perhaps it’s also affected by your settings. Maybe it’s regional as well, or based on your search result. And, as AI’s non-deterministic, you can’t expect it to always work.
I just tested it on Bing too, for shits and giggles
you can’t butter the whole world’s bread meaning
The phrase “you can’t butter the whole world’s bread” means that one cannot have everything
It didn’t work for me. Why not?
Worked for me, but I couldn’t include any names or swearing.
I for one will not be putting any gibberish into Google’s AI for any reason. I don’t find it fun. I find it annoying and have taken steps to avoid it completely on purpose. I don’t understand these articles that want to throw shade at AI LLM’s by suggesting their viewers go use the LLM’s which only helps the companies that own the LLM’s.
Like. Yes. We have established that LLM’s will give misinformation and create slop because all their data sets are tainted. Do we need to continue to further this nonsense?
Try this on your friends, make up an idiom, then walk up to them, say it without context, and then say “meaning?” and see how they respond.
Pretty sure most of mine will just make up a bullshit response nd go along with what I’m saying unless I give them more context.
There are genuinely interesting limitations to LLMs and the newer reasoning models, and I find it interesting to see what we can learn from them, this is just ham fisted robo gotcha journalism.
My friends would probably say something like “I’ve never heard that one, but I guess it means something like …”
The problem is, these LLMs don’t give any indication when they’re making stuff up versus when repeating an incontrovertible truth. Lots of people don’t understand the limitations of things like Google’s AI summary* so they will trust these false answers. Harmless here, but often not.
* I’m not counting the little disclaimer because we’ve been taught to ignore smallprint from being faced with so much of it
My friends would probably say something like “I’ve never heard that one, but I guess it means something like …”
Ok, but the point is that lots of people would just say something and then figure out if it’s right later.
The problem is, these LLMs don’t give any indication when they’re making stuff up versus when repeating an incontrovertible truth. Lots of people don’t understand the limitations of things like Google’s AI summary* so they will trust these false answers. Harmless here, but often not.
Quite frankly, you sound like middle school teachers being hysterical about Wikipedia being wrong sometimes.
LLMs are already being used for policy making, business decisions, software creation and the like. The issue is bigger than summarisers, and “hallucinations” are a real problem when they lead to real decisions and real consequences.
If you can’t imagine why this is bad, maybe read some Kafka or watch some Black Mirror.
If you can’t imagine why this is bad, maybe read some Kafka or watch some Black Mirror.
Lmfao. Yeah, ok, let’s get my predictions from the depressing show dedicated to being relentlessly pessimistic at every single decision point.
And yeah, like I said, you sound like my hysterical middle school teacher claiming that Wikipedia will be society’s downfall.
Guess what? It wasn’t. People learn that tools are error prone and came up with strategies to use them while correcting for potential errors.
Like at a fundamental, technical level, components of a system can be error prone, but still be useful overall. Quantum calculations have inherent probabilities and errors in them, but they can still solve some types of calculations so much faster than normal computers that you can run the same calculation 100x on a Quantum Computer, average out the results to remove the outlying errors, and get to the right answer far faster than a classical computer.
Computer chips in satellites and the space station are constantly having random bits of memory flipped by cosmic rays, but they still work fine because their RAM is error-correcting ram, that can use similar methods to verify and check for errors.
And at a super high level, some of my friends and coworkers are more reliable than others, that doesn’t mean the ones that are less reliable aren’t helpful, it just means I have to take what they say with a grain of salt.
Designing for error correction is a thing, and people are perfectly capable of doing so in their personal lives.
and this is why humans are bad, a tool is neither good or bad, sure a tool can use a large amount of resources to develop only to be completely obsolete in a year but only humans (so far) have the ability (and stupidity) to be both in charge of millions of lives and trust a bunch of lithographed rocks to create tarrif rates for uninhabited islands (and the rest of the world).
it highlights the fact that these LLMs refuse to say “I don’t know”, which essentially means we cannot rely on them for any factual reporting.
But a) they don’t refuse, most will tell you if you prompt them well them and b) you cannot rely on them as the sole source of truth but an information machine can still be useful if it’s right most of the time.
My friends aren’t burning up the planet just to come up with that useless response though.
Yes, they literally are. Or maybe you haven’t heard of human caused climate change?
You dumb
So, you have friends who are as stupid as an AI. Got it. What’s your point?
Yeah, mine would say, “what you talkin’ 'bout Willis?”:
